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Статті в журналах з теми "Fast retrieval"
Fournier, N., P. Stammes, M. de Graaf, R. van der A, A. Piters, M. Grzegorski, and A. Kokhanovsky. "Improving cloud information over deserts from SCIAMACHY Oxygen A-band measurements." Atmospheric Chemistry and Physics 6, no. 1 (January 25, 2006): 163–72. http://dx.doi.org/10.5194/acp-6-163-2006.
Повний текст джерелаGeigle, Gregor, Jonas Pfeiffer, Nils Reimers, Ivan Vulić, and Iryna Gurevych. "Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrieval." Transactions of the Association for Computational Linguistics 10 (2022): 503–21. http://dx.doi.org/10.1162/tacl_a_00473.
Повний текст джерелаDesmons, Marine, Ping Wang, Piet Stammes, and L. Gijsbert Tilstra. "FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2." Atmospheric Measurement Techniques 12, no. 4 (April 23, 2019): 2485–98. http://dx.doi.org/10.5194/amt-12-2485-2019.
Повний текст джерелаJonkheid, B. J., R. A. Roebeling, and E. van Meijgaard. "A fast SEVIRI simulator for quantifying retrieval uncertainties in the CM SAF cloud physical property algorithm." Atmospheric Chemistry and Physics 12, no. 22 (November 20, 2012): 10957–69. http://dx.doi.org/10.5194/acp-12-10957-2012.
Повний текст джерелаMasiello, Guido, Carmine Serio, Sara Venafra, Laurent Poutier, and Frank-M. Göttsche. "SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval." Sensors 19, no. 7 (March 29, 2019): 1532. http://dx.doi.org/10.3390/s19071532.
Повний текст джерелаFournier, N., P. Stammes, M. de Graaf, R. van der A, A. Piters, R. Koelemeijer, and A. Kokhanovsky. "Improving cloud information over deserts from SCIAMACHY O<sub>2</sub> A-band." Atmospheric Chemistry and Physics Discussions 5, no. 4 (August 16, 2005): 6013–39. http://dx.doi.org/10.5194/acpd-5-6013-2005.
Повний текст джерелаSmith, William L., Elisabeth Weisz, Stanislav V. Kireev, Daniel K. Zhou, Zhenglong Li, and Eva E. Borbas. "Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances." Journal of Applied Meteorology and Climatology 51, no. 8 (August 2012): 1455–76. http://dx.doi.org/10.1175/jamc-d-11-0173.1.
Повний текст джерелаSun, Jian Fei, Zhi Yi Qu, and Kun Yu Wang. "Fast Image Retrieval Based Weighted Color AutoCorrelogram and LSH Indexing." Applied Mechanics and Materials 667 (October 2014): 208–12. http://dx.doi.org/10.4028/www.scientific.net/amm.667.208.
Повний текст джерелаPapadias, D., M. Mantzourogiannis, and I. Ahmad. "Fast retrieval of similar configurations." IEEE Transactions on Multimedia 5, no. 2 (June 2003): 210–22. http://dx.doi.org/10.1109/tmm.2003.811629.
Повний текст джерелаSwanson, Mitchell D. "Fast progressively refined image retrieval." Journal of Electronic Imaging 7, no. 3 (July 1, 1998): 443. http://dx.doi.org/10.1117/1.482611.
Повний текст джерелаДисертації з теми "Fast retrieval"
Pesavento, Marius. "Fast algorithms for multidimensional harmonic retrieval." [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=975415328.
Повний текст джерелаCao, Hui, Noboru Ohnishi, Yoshinori Takeuchi, Tetsuya Matsumoto, and Hiroaki Kudo. "FAST HUMAN POSE RETRIEVAL USING APPROXIMATE CHAMFER DISTANCE." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2006. http://hdl.handle.net/2237/10437.
Повний текст джерелаPerry, S. T. "Fast interactive object delineation in images for content based retrieval and navigation." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286748.
Повний текст джерелаKuan, Joseph. "Image texture analysis and fast similarity search for content based retrieval and navigation." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287321.
Повний текст джерелаLardeux, Florian. "Robust Modelling and Efficient Recognition of Quasi-Flat Objects — Application to Ancient Coins." Thesis, La Rochelle, 2022. http://www.theses.fr/2022LAROS002.
Повний текст джерелаQuasi-flat objects are obtained from a matrix which defines specific features observable in their engraving. Some examples of these are dry stamps, amphora stamps or ancient coins. Quasi-flat objects are subsequently understood as very flat shapes onto which a characteristic relief is inscribed. Recognizing such objects is not an easy feat as many barriers come into play. The relief of quasi-flat objects is prone to non-rigid deformations and the illumination conditions influence the perception of the object’s relief. Furthermore, these items may have undergone various deteriorations, leading to the occlusion of some parts of their relief. In this thesis, we tackle the issue of recognizing quasi-flat objects. This work is articulated around three major axes. The first one aims at creating a model to represent the objects both by highlighting their main characteristics and taking into account the afore mentioned barriers. To this aim, the concept of multi-light energy map is introduced. The second and third axes introduce strategies for the recognition. On the one hand, we propose the use of contours as main features. Contours are described via a signature model from which specific descriptors are calculated. In order to store, retrieve and match those features, a data structure based on associative arrays, the LACS system, is introduced, which enables a fast retrieval of similar contours. On the other hand, the use of textures is investigated. The scope here is centered on the use of specific 2D regions and their description in order to perform the recognition. A similar angle is taken to store and retrieve the information as a similar, yet a more complex data structure is introduced
au, n. jackson@murdoch edu, and Natalie Deanne Jackson. "Simple arithmetic processing : fact retrieval mechanisms and the influence of individual difference, surface from, problem type and split on processing." Murdoch University, 2006. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20070717.114439.
Повний текст джерелаJackson, Natalie Deanne. "Simple arithmetic processing: fact retrieval mechanisms and the influence of individual difference, surface form, problem type and split on processing." Jackson, Natalie Deanne (2007) Simple arithmetic processing: fact retrieval mechanisms and the influence of individual difference, surface form, problem type and split on processing. PhD thesis, Murdoch University, 2007. http://researchrepository.murdoch.edu.au/108/.
Повний текст джерелаPinheiro, Josiane Melchiori. "A influência das folksonomias na eficiência da fase inicial de modelagem conceitual." Universidade Tecnológica Federal do Paraná, 2016. http://repositorio.utfpr.edu.br/jspui/handle/1/2831.
Повний текст джерелаEste estudo examina a hipótese que usar folksonomias induzidas dos sistemas de tagging colaborativo em modelagem conceitual deve reduzir o número de divergências entre os atores envolvidos no processo quando eles elicitam termos para serem usados no modelo, usando-se como baseline os termos extraídos de páginas Web baseados na frequência de termos. Usa como medida de eficiência o número de divergências, pois quanto menor o número de divergências, menor o tempo e o esforço necessários para criar o modelo conceitual. Descreve os experimentos controlados de modelagem conceitual que foram realizados com grupos experimentais que receberam a folksonomia e com grupos de controle que receberam termos extraídos de páginas Web. Os resultados descritos mostram que grupos experimentais e de controle obtiveram números similares de divergências. Outras medidas de eficiências, assim como o reuso dos termos nos artefatos da modelagem e a facilidade percebida ao realizar a tarefa de modelagem confirmaram os resultados obtidos pelo número de divergências, com uma eficiência ligeiramente maior entre os grupos experimentais.
This study examines the hypothesis that using folksonomies induced from collaborative tagging systems in conceptual modeling should reduce the number of divergences between actors when they elicit terms to be used in a model, using as baseline terms extracted from webpages based on term frequency. It uses as efficiency measure the number of divergences, because the fewer the divergences, the less time and effort required to create a conceptual model. It describes the controlled conceptual modeling experiments that were performed using experimental groups that received a folksonomy and control groups that received terms extracted from webpages. The results show that the experimental and control groups obtained similar numbers of divergences. Other efficiency measures, such as reuse of terms in the phases of conceptual modeling and perceived ease of performing the modeling task, confirmed the results obtained by the number of divergences, with slightly greater efficiency among the experimental groups.
Ho, Chia-Lin, and 何佳霖. "Compression and Fast Retrieval for Digital Waveform." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/73261928713281426620.
Повний текст джерела國立臺灣大學
資訊工程學研究所
90
Among VLSI circuit design, functional verification has become an important part due to rapid extension of circuits functionalities in many consumer and industry products. During simulation for digital circuits, the waveforms are stored on disk for future investigation and will finally fill up huge amounts of disk space. Beside of disk consumption, browsing the waveform becomes difficult because the required data is distributed over a large file space. Hence, We developed a set of algorithms and techniques that can be used to compress digital waveform, and we also define a new waveform data format that provides random access to improve the retrievable speed. Experimental result show that the retrievable time can be increased above 100 times and we could almost achieve 10%~35% compression ration comparing to the size of traditional VCD format waveform.
Shieh, Wann-Yun, and 謝萬雲. "Fast Information Retrieval in Incremental Web Databases." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/92235606317310550552.
Повний текст джерела國立交通大學
資訊工程系
92
This dissertation proposes methodologies to (1) speedup information retrieval, (2) perform most-correlated-document-first retrieval, and (3) perform incremental index-update, for dynamically growing Web databases. This dissertation focuses on the indexing structure refinements by dealing with a most-widely-used one, called the inverted file. First, to speedup information retrieval, the dissertation deals with the inverted file by index compression, query-result caching. The objective is to minimize the query response time for database scale and current user behavior. Second, to perform most-correlated-document-first retrieval, the dissertation deals with the inverted file by tree-based index structuring. The objective is to retrieve the most correlated documents for user queries as soon as possible. Finally, to provide incremental index-update, the dissertation deals with the inverted file by spare-space allocation. The objective is to best guarantee that the index has sufficient reserved space to amortize update costs, and also to keep high space efficiency. Research topics in the dissertation are (1) Inverted file compression through document identifier reassignment The first topic is to propose a document identifier reassignment algorithm to compress the ever-increasing inverted files. Conventionally, the d-gap technique is used in the inverted file compression by replacing document identifiers with usually much smaller gap values. The objective of this topic is to reassign document identifiers, based on the document similarity evaluation, to smoothen and reduce the gap values in an inverted file. A Web database can take benefits from it in terms of the saved storage space, and fast file look-up time. (2) Inverted file caching for fast information retrieval The second topic is to propose an inverted file caching mechanism to exploit the locality of user queries in a Web database. In this mechanism, we enhance the indexing speed by a linked-list-based probing process, and enhance memory efficiency by a chunk-based space management. A Web database can take benefits from it in terms of the fast popular data’s response. (3) Tree-based inverted file structuring for most-correlated-document-first retrieval The third topic is to propose an n-key-heap posting-tree structure to preserve the identifier numerical orders and ranking information simultaneously in an index file. The objective of this topic is to reconstruct an inverted file to store important and most-correlated data efficiently such that they can be retrieved without time-consuming ranking or sorting. A Web database can take benefits from it in terms of the fast most-correlated-data’s response. (4) Statistics-based spare-space allocation for incremental inverted file updates The fourth topic is to propose a statistics-based approach to allocate the free space in an inverted file for future updates. The approach estimates the space requirements for an inverted file by collecting only a little most-recent statistical data. The objective is to incrementally update an inverted file without complex file reorganization or expensive free-space management, as the database expands. A Web database can take benefits from it in terms of the fast index updates. The results of this dissertation include: (1)For inverted file compression, the proposed approach improves the compression rate by 18%, and improves the query response time by 15% on average. (2)For inverted file caching, the proposed approach takes only about 7% additional space costs to outperform the conventional caching mechanisms by 20% indexing speed improvements on average. (3)For tree-based inverted file structuring, the time to retrieve the most-correlated documents is improved by 8%~45%, compared with the conventional link-list-based index structure. (4)For incremental inverted file updates, the proposed approach outperforms the conventional approaches by 16% space utilization improvements, and 15% index-updating speed improvements on average.
Книги з теми "Fast retrieval"
Scherer, Rafał. Computer Vision Methods for Fast Image Classification and Retrieval. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-12195-2.
Повний текст джерелаFast facts online: Search strategies for finding business information. Homewood, Ill: D. Jones-Irwin, 1986.
Знайти повний текст джерелаHeinström, Jannica. Fast surfers, broad scanners, and deep divers: Personality and information-seeking behaviour. Åbo [Finland]: Åbo Akademis förlag, 2002.
Знайти повний текст джерелаBerkman, Robert I. Find it fast: How to uncover expert information on any subject. 3rd ed. New York: HarperPerennial, 1994.
Знайти повний текст джерелаBerkman, Robert I. Find it fast: How to uncover expert information on any subject. New York: Perennial Library, 1990.
Знайти повний текст джерелаBerkman, Robert I. Find it fast: How to uncover expert information on any subject. New York: Harper & Row, 1987.
Знайти повний текст джерелаBerkman, Robert I. Find it fast: How to uncover expert information on any subject. 4th ed. New York: HarperPerennial, 1997.
Знайти повний текст джерелаAnupam, Datta, Etalle Sandro, and SpringerLink (Online service), eds. Formal Aspects of Security and Trust: 8th International Workshop, FAST 2011, Leuven, Belgium, September 12-14, 2011. Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Знайти повний текст джерелаFind it fast: How to uncover expert information on any subject online or in print. 5th ed. New York, NY: HarperResource, 2000.
Знайти повний текст джерелаDegano, Pierpaolo. Formal Aspects of Security and Trust: 7th International Workshop, FAST 2010, Pisa, Italy, September 16-17, 2010. Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.
Знайти повний текст джерелаЧастини книг з теми "Fast retrieval"
Trotman, Andrew, Xiang-Fei Jia, and Shlomo Geva. "Fast and Effective Focused Retrieval." In Focused Retrieval and Evaluation, 229–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14556-8_24.
Повний текст джерелаBelazzougui, Djamal, Paolo Boldi, and Sebastiano Vigna. "Dynamic Z-Fast Tries." In String Processing and Information Retrieval, 159–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16321-0_15.
Повний текст джерелаSong, Siwoo, Cheol Ryu, Simone Faro, Thierry Lecroq, and Kunsoo Park. "Fast Cartesian Tree Matching." In String Processing and Information Retrieval, 124–37. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32686-9_9.
Повний текст джерелаMozgovoy, Maxim, Kimmo Fredriksson, Daniel White, Mike Joy, and Erkki Sutinen. "Fast Plagiarism Detection System." In String Processing and Information Retrieval, 267–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11575832_30.
Повний текст джерелаMunro, J. Ian, Yakov Nekrich, and Jeffrey S. Vitter. "Fast Construction of Wavelet Trees." In String Processing and Information Retrieval, 101–10. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11918-2_10.
Повний текст джерелаKarch, Daniel, Dennis Luxen, and Peter Sanders. "Improved Fast Similarity Search in Dictionaries." In String Processing and Information Retrieval, 173–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16321-0_16.
Повний текст джерелаKaneta, Yusaku. "Fast Wavelet Tree Construction in Practice." In String Processing and Information Retrieval, 218–32. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00479-8_18.
Повний текст джерелаBroß, Jan, Simon Gog, Matthias Hauck, and Marcus Paradies. "Fast Construction of Compressed Web Graphs." In String Processing and Information Retrieval, 116–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67428-5_11.
Повний текст джерелаBelazzougui, Djamal, and Fabio Cunial. "Fast Label Extraction in the CDAWG." In String Processing and Information Retrieval, 161–75. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67428-5_14.
Повний текст джерелаYamazaki, Tomohiro, Hisashi Koga, and Takahisa Toda. "Fast Exact Algorithm to Solve Continuous Similarity Search for Evolving Queries." In Information Retrieval Technology, 84–96. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70145-5_7.
Повний текст джерелаТези доповідей конференцій з теми "Fast retrieval"
Chen, Yong-Fan, and Ite A. Yu. "Manipulate retrieval of stored light pulses." In Slow and Fast Light. Washington, D.C.: OSA, 2008. http://dx.doi.org/10.1364/sl.2008.sma6.
Повний текст джерелаHahn, J., and B. S. Ham. "Enhanced Echo Retrieval Efficiency Using Ultraslow Light." In Slow and Fast Light. Washington, D.C.: OSA, 2011. http://dx.doi.org/10.1364/sl.2011.slmc7.
Повний текст джерелаEdmundson, David, and Gerald Schaefer. "Flickr Retriever -- Fast Retrieval of Flickr Photos." In 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2012. http://dx.doi.org/10.1109/wi-iat.2012.234.
Повний текст джерелаVudyasetu, P. K., R. M. Camacho, and J. C. Howell. "Storage and retrieval of images in hot atomic Rubidium vapor." In Slow and Fast Light. Washington, D.C.: OSA, 2008. http://dx.doi.org/10.1364/sl.2008.swd4.
Повний текст джерелаEdmundson, David, and Gerald Schaefer. "Fast mobile image retrieval." In 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW). IEEE, 2013. http://dx.doi.org/10.1109/icmew.2013.6618399.
Повний текст джерелаViswanathan, Aditya, and Mark Iwen. "Fast compressive phase retrieval." In 2015 49th Asilomar Conference on Signals, Systems and Computers. IEEE, 2015. http://dx.doi.org/10.1109/acssc.2015.7421436.
Повний текст джерелаGao, Junyu, and Changsheng Xu. "Fast Video Moment Retrieval." In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. http://dx.doi.org/10.1109/iccv48922.2021.00155.
Повний текст джерелаWehrmann, Jonatas, Mauricio A. Lopes, Martin D. More, and Rodrigo C. Barros. "Fast Self-Attentive Multimodal Retrieval." In 2018 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2018. http://dx.doi.org/10.1109/wacv.2018.00207.
Повний текст джерелаKamel, Ibrahim. "Fast retrieval of cursive handwriting." In the fifth international conference. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/238355.238447.
Повний текст джерелаDimov, Dimo. "Fast, shape based image retrieval." In the 4th international conference conference. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/973620.973669.
Повний текст джерелаЗвіти організацій з теми "Fast retrieval"
Guan, Ziqiao, and Esther H. Tsai. PtychoNet: Fast and High Quality Phase Retrieval for Ptychography. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1599580.
Повний текст джерелаDas, M., B. A. Draper, W. J. Lim, R. Manmatha, and E. M. Riseman. A Fast, Background-Independent Retrieval Strategy for Color Image Databases. Fort Belvoir, VA: Defense Technical Information Center, November 1996. http://dx.doi.org/10.21236/ada477660.
Повний текст джерелаKarypis, George, and Euihong Han. Concept Indexing: A Fast Dimensionality Reduction Algorithm With Applications to Document Retrieval and Categorization. Fort Belvoir, VA: Defense Technical Information Center, March 2000. http://dx.doi.org/10.21236/ada439511.
Повний текст джерелаPoole, Paula M., Marcie S. Kronberg, and Debra Meyers. Automated Airdrop Information Retrieval System-Human Fact ors Database (AAIRS-HFD) (Users Manual). Fort Belvoir, VA: Defense Technical Information Center, September 1994. http://dx.doi.org/10.21236/ada285571.
Повний текст джерела